A Test for the Cobb Douglas Production Function in Manufacturing Sector: The Case of Bangladesh

Shaiara Husain; Md. Shahidul Islam

doi:doi:10.11648/j.ijber.20160505.13

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A Test for the Cobb Douglas Production Function in Manufacturing Sector: The Case of Bangladesh

Shaiara Husain, Md. Shahidul Islam

Published in International Journal of Business and Economics Research (Volume 5, Issue 5)

Received: 16 August 2016 Accepted: 1 September 2016 Published: 21 September 2016

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Abstract

The manufacturing sector has been a major driver of GDP growth in Bangladesh. The sector recorded an impressive average annual growth during last a couple of decades. This study is an attempt to test empirically the Cobb-Douglas production function for manufacturing sector of Bangladesh. Data of total value of output, total asset, total liabilities, number of permanent workers etc. of about six major types of industries including Garments, Textiles, Food & Food Processing, Leather & Leather Products, Electronics and Chemicals& Pharmaceuticals have been used. Researchers use total value of output as Y, total liabilities as K, and number of permanent workers (including officials managers, personal) as L. Study finds that coefficient for K and L are 0.49 and 0.51 respectively for entire manufacturing sector. In case of Garments, coefficient for K is 0.30 and L is 0.61 implying that labor is more productive than capital. The statement is also true for Textile sector and Leather & leather products. Capital is, on other hand, more productive than labor in Food & food processing industries, Electronics, Chemicals & Pharmaceuticals sectors. The coefficients are significant and do not suffer from MC and also not from Autocorrelation. To correct heteroscedasticity, WLS method (weighted Least Square) has been adopted. Findings reveal that Cobb-Douglas production function is applicable and exhibits increasing returns to scale in the context of manufacturing sector of Bangladesh.

Published in	International Journal of Business and Economics Research (Volume 5, Issue 5)
DOI	10.11648/j.ijber.20160505.13
Page(s)	149-154
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Manufacturing Sector, Cobb-Douglas Production Function, Productivity, Labor, Capital

References

[1]	Miller, E. (2008) ‘An Assessment of CES and Cobb-Douglas Production Functions’, Congressional Budget Office. Retrieved from:https://www.cbo.gov/sites/default/files/cbofiles/ftpdocs/94xx/doc9497/2008-05.pdf
[2]	Hossain, M. S. & Islam, A. N. (2013) ‘Productivity Analysis and Measuring the Returns to Scale of Manufacturing Firms in the South-West Region of Bangladesh’, IOSR Journal Of Humanities And Social Science (IOSR-JHSS),vol.17, no.1, pp. 69-77.
[3]	Hagendorf, K. (2009) ‘The Cobb-Douglas Production Function and Political Economy’, Journal of Political Economy, vol.69, no.8, pp. 69-79.
[4]	Hossain, S. I. (1987) Allocative and Technical Efficiency: ‘A Study of Rural Enterprises in Bangladesh’, The Journal of Developing Economics, vol.25, no.1, pp. 56-72.
[5]	Kehindi, A. L. & T. T. Awoyem. (2009) ‘Analysis of Economics Efficiency in Sawn wood Production in Southwest Nigeria’, Journal of Human Ecology, vol.26, no.3, pp. 175- 183.
[6]	Baten, M. A., Rana, M. Das, S. & Khaleque, M. A. (2006) ‘Technical Efficiency of Some Selected Manufacturing Industries in Bangladesh: A Stochastic Frontier Analysis’, The Lahore Journal of Economics, vol.11, no 2, pp 23-41.
[7]	Hossain, M. M., Majumder, A. K. & Basak, T. (2012) ‘An Application of Non-Linear Cobb-Douglas Production Function to Selected Manufacturing Industries in Bangladesh’, Open Journal of Statistics, vol. 2, pp. 460-468.
[8]	Wu, D. M. (1975) ‘Estimation of the Cobb-Douglas Production Function’, Econometrica, vol. 43, no. 4, pp. 739-744.
[9]	Bhashin, V. K. & Seth, V. K. (1980) ‘Estimation of production Functions for Indian Manufacturing Industries’, Indian Journal of Industrial Relations, vol. 15, no. 3, pp. 395-409.
[10]	Hossain, M. Z., Bhatti, M. I. & Ali, M. Z. (2004) ‘An Econometric Analysis of Some Major Manufacturing Industries: A Case Study’, Managerial Auditing Journal, vol. 19, no. 6, pp. 790-795.

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APA Style

Shaiara Husain, Md. Shahidul Islam. (2016). A Test for the Cobb Douglas Production Function in Manufacturing Sector: The Case of Bangladesh. International Journal of Business and Economics Research, 5(5), 149-154. https://doi.org/10.11648/j.ijber.20160505.13

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ACS Style

Shaiara Husain; Md. Shahidul Islam. A Test for the Cobb Douglas Production Function in Manufacturing Sector: The Case of Bangladesh. Int. J. Bus. Econ. Res. 2016, 5(5), 149-154. doi: 10.11648/j.ijber.20160505.13

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AMA Style

Shaiara Husain, Md. Shahidul Islam. A Test for the Cobb Douglas Production Function in Manufacturing Sector: The Case of Bangladesh. Int J Bus Econ Res. 2016;5(5):149-154. doi: 10.11648/j.ijber.20160505.13

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@article{10.11648/j.ijber.20160505.13,
  author = {Shaiara Husain and Md. Shahidul Islam},
  title = {A Test for the Cobb Douglas Production Function in Manufacturing Sector: The Case of Bangladesh},
  journal = {International Journal of Business and Economics Research},
  volume = {5},
  number = {5},
  pages = {149-154},
  doi = {10.11648/j.ijber.20160505.13},
  url = {https://doi.org/10.11648/j.ijber.20160505.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijber.20160505.13},
  abstract = {The manufacturing sector has been a major driver of GDP growth in Bangladesh. The sector recorded an impressive average annual growth during last a couple of decades. This study is an attempt to test empirically the Cobb-Douglas production function for manufacturing sector of Bangladesh. Data of total value of output, total asset, total liabilities, number of permanent workers etc. of about six major types of industries including Garments, Textiles, Food & Food Processing, Leather & Leather Products, Electronics and Chemicals& Pharmaceuticals have been used. Researchers use total value of output as Y, total liabilities as K, and number of permanent workers (including officials managers, personal) as L. Study finds that coefficient for K and L are 0.49 and 0.51 respectively for entire manufacturing sector. In case of Garments, coefficient for K is 0.30 and L is 0.61 implying that labor is more productive than capital. The statement is also true for Textile sector and Leather & leather products. Capital is, on other hand, more productive than labor in Food & food processing industries, Electronics, Chemicals & Pharmaceuticals sectors. The coefficients are significant and do not suffer from MC and also not from Autocorrelation. To correct heteroscedasticity, WLS method (weighted Least Square) has been adopted. Findings reveal that Cobb-Douglas production function is applicable and exhibits increasing returns to scale in the context of manufacturing sector of Bangladesh.},
 year = {2016}
}

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TY - JOUR
T1 - A Test for the Cobb Douglas Production Function in Manufacturing Sector: The Case of Bangladesh
AU - Shaiara Husain
AU - Md. Shahidul Islam
Y1 - 2016/09/21
PY - 2016
N1 - https://doi.org/10.11648/j.ijber.20160505.13
DO - 10.11648/j.ijber.20160505.13
T2 - International Journal of Business and Economics Research
JF - International Journal of Business and Economics Research
JO - International Journal of Business and Economics Research
SP - 149
EP - 154
PB - Science Publishing Group
SN - 2328-756X
UR - https://doi.org/10.11648/j.ijber.20160505.13
AB - The manufacturing sector has been a major driver of GDP growth in Bangladesh. The sector recorded an impressive average annual growth during last a couple of decades. This study is an attempt to test empirically the Cobb-Douglas production function for manufacturing sector of Bangladesh. Data of total value of output, total asset, total liabilities, number of permanent workers etc. of about six major types of industries including Garments, Textiles, Food & Food Processing, Leather & Leather Products, Electronics and Chemicals& Pharmaceuticals have been used. Researchers use total value of output as Y, total liabilities as K, and number of permanent workers (including officials managers, personal) as L. Study finds that coefficient for K and L are 0.49 and 0.51 respectively for entire manufacturing sector. In case of Garments, coefficient for K is 0.30 and L is 0.61 implying that labor is more productive than capital. The statement is also true for Textile sector and Leather & leather products. Capital is, on other hand, more productive than labor in Food & food processing industries, Electronics, Chemicals & Pharmaceuticals sectors. The coefficients are significant and do not suffer from MC and also not from Autocorrelation. To correct heteroscedasticity, WLS method (weighted Least Square) has been adopted. Findings reveal that Cobb-Douglas production function is applicable and exhibits increasing returns to scale in the context of manufacturing sector of Bangladesh.
VL - 5
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ER -

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Author Information

Shaiara Husain

Department of Economics, Southeast University, Dhaka, Bangladesh
Md. Shahidul Islam

Department of Economics, Southeast University, Dhaka, Bangladesh

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Plain Text BibTeX RIS

APA Style

Shaiara Husain, Md. Shahidul Islam. (2016). A Test for the Cobb Douglas Production Function in Manufacturing Sector: The Case of Bangladesh. International Journal of Business and Economics Research, 5(5), 149-154. https://doi.org/10.11648/j.ijber.20160505.13

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ACS Style

Shaiara Husain; Md. Shahidul Islam. A Test for the Cobb Douglas Production Function in Manufacturing Sector: The Case of Bangladesh. Int. J. Bus. Econ. Res. 2016, 5(5), 149-154. doi: 10.11648/j.ijber.20160505.13

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AMA Style

Shaiara Husain, Md. Shahidul Islam. A Test for the Cobb Douglas Production Function in Manufacturing Sector: The Case of Bangladesh. Int J Bus Econ Res. 2016;5(5):149-154. doi: 10.11648/j.ijber.20160505.13

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@article{10.11648/j.ijber.20160505.13,
  author = {Shaiara Husain and Md. Shahidul Islam},
  title = {A Test for the Cobb Douglas Production Function in Manufacturing Sector: The Case of Bangladesh},
  journal = {International Journal of Business and Economics Research},
  volume = {5},
  number = {5},
  pages = {149-154},
  doi = {10.11648/j.ijber.20160505.13},
  url = {https://doi.org/10.11648/j.ijber.20160505.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijber.20160505.13},
  abstract = {The manufacturing sector has been a major driver of GDP growth in Bangladesh. The sector recorded an impressive average annual growth during last a couple of decades. This study is an attempt to test empirically the Cobb-Douglas production function for manufacturing sector of Bangladesh. Data of total value of output, total asset, total liabilities, number of permanent workers etc. of about six major types of industries including Garments, Textiles, Food & Food Processing, Leather & Leather Products, Electronics and Chemicals& Pharmaceuticals have been used. Researchers use total value of output as Y, total liabilities as K, and number of permanent workers (including officials managers, personal) as L. Study finds that coefficient for K and L are 0.49 and 0.51 respectively for entire manufacturing sector. In case of Garments, coefficient for K is 0.30 and L is 0.61 implying that labor is more productive than capital. The statement is also true for Textile sector and Leather & leather products. Capital is, on other hand, more productive than labor in Food & food processing industries, Electronics, Chemicals & Pharmaceuticals sectors. The coefficients are significant and do not suffer from MC and also not from Autocorrelation. To correct heteroscedasticity, WLS method (weighted Least Square) has been adopted. Findings reveal that Cobb-Douglas production function is applicable and exhibits increasing returns to scale in the context of manufacturing sector of Bangladesh.},
 year = {2016}
}

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